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1 Geography, Department of Geosciences and Natural Resource Management, Faculty of Science, Københavns Universitet 2 Centre for Geo-Information 3 Institute of Evolutionary Biology and Environmental Studies 4 Institute for Biological Problems of the Cryolithozone, Siberian Branch Russian Academy of Sciences 5 Institute of Physicochemical and Biological Problems of Soil Science 6 Geography, Department of Geosciences and Natural Resource Management, Faculty of Science, Københavns Universitet
Predicted global warming will be most pronounced in the Arctic and will severely affect permafrost environments. Due to its large spatial extent and large stocks of soil organic carbon, changes to organic matter decomposition rates and associated carbon fluxes in Arctic permafrost soils will significantly impact the global carbon cycle. We explore the potential of soil spectroscopy to estimate soil carbon properties and investigate the relation between soil properties and vegetation composition. Soil samples are collected in Siberia, and vegetation descriptions are made at each sample point. First, laboratory-determined soil properties are related to the spectral reflectance of wet and dried samples using partial least squares regression (PLSR) and stepwise multiple linear regression (SMLR). SMLR, using selected wavelengths related with C and N, yields high calibration accuracies for C and N. PLSR yields a good prediction model for K and a moderate model for pH. Using these models, soil properties are determined for a larger number of samples, and soil properties are related to plant species composition. This analysis shows that variation of soil properties is large within vegetation classes, but vegetation composition can be used for qualitative estimation of soil properties. © 2012 Harm Bartholomeus et al.
Applied and Environmental Soil Science, 2012, Vol 2012
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